Black box models like deep neural networks and ensemble techniques like Random Forest and XGBoost are increasingly popular because of their predictive power. However, they lack the transparency of simpler models, and this has created a dilemma. How does one produce the highest possible accuracy while providing the critical explainability demanded in most industries? How does one meet the ethical requirements of machine learning without explainability?
Explainable AI (XAI) is the solution that is increasingly sought by data scientists. The KNIME Analytics Platform is the perfect resource to learn and utilize XAI techniques.
The main topics covered in this webinar are:
Why the need for XAI is rapidly increasing
What is a taxonomy of methods for XAI and IML and when you should use them
How KNIME helps produce XAI solutions?
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Absolutely - fire away!
Download the latest free, open source version of KNIME here: knime.com/download.